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The Smart Cable NMT Module and Accessories are indicated for monitoring the relaxation of the patient when neuromuscular blockades are administered.

The Smart Cable NMT Module and Accessories are comprised of:

• · AF-201P NMT Module with Smart Cable
• Disposable Electrodes
• Main cable
• · Holder (optional)

The Smart Cable NMT Module and Accessories are intended to be used as a system that requires Nihon Kohden compatible electrodes and bedside monitoring systems. The Smart Cable NMT Module and Accessories are intended for use by medical personnel in clinical settings and are available by prescription only.

The Life Scope BSM-3000 Series Bedside Monitor is intended to monitor, display and record physiological data to provide cardiac and vital signs monitoring within a medical facility. The device is intended to produce a visual record of the electrical signals produced by the heart and monitor the electrocardiogram to generate audible and/or visible alarms when an arrhythmia exists.

The device is also intended to monitor heart rate, blood oxygen saturation (SpO2), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), body temperature,BIS, cardiac output (CO), oxygen concentration (O2), carbon dioxide concentration (CO2), EtCO2, respiratory rate, and inspired and expired anesthetic gases including N20. Halothane. Isoflurane. Enflurane. Sevoflurane, and Desflurane.

The device may generate an audible and/or visual alarm when a measured rate falls outside preset limits. The device may also be used to condition and transmit physiological signals via radio frequency. The device can interface to external equipment to display numerical and waveform data and alarms from the external devices. Supported external devices include CO2 monitors, BIS monitors, Anesthetic agents/gases detection system, Anesthesia machine, Ventilators, CCO monitors, TOF monitors, CCO/SvO2 Monitors, EEG monitoring device, tcPO2/tcPCO2 monitors, rSO2 monitors and external devices which output analog voltage signal.

The device will be available for use by medical personnel on patients within a medical facility on all patient populations.

The Life Scope BSM-6000 Series Bedside Monitor is intended to monitor, display and record physiological data to provide cardiac and vital signs monitoring within a medical facility. The device is intended to produce a visual record of the electrical signals produced by the heart and monitor the electrocardiogram to generate audible and/or visible alarms when an arrhythmia exists.

The device is also intended to monitor heart rate, plood oxygen saturation (SpO2), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), body temperature,BIS, cardiac output (CO), oxygen concentration (FiO2), carbon dioxide concentration (CO2). EtCO2. respiratory rate, and inspired and expired anesthetic agents and anesthetic gases including N20, Halothane, Isoflurane, Enflurane, Sevoflurane, and Desflurane.

The device may generate an audible and/or visual alarm when a measured rate falls outside preset limits. The device may also be used to condition and transmit physiological signals via radio frequency. The device can interface to external equipment to display numerical and waveform data and alarms from the external devices. Supported external devices include CO2 monitors, BIS monitors, Anesthetic agents/gases detection system, Anesthesia machine, Ventilators, CCO monitors, TOF monitors, CCO/SvO2 Monitors, EEG monitoring device, tcPO2/tcPCO2 monitors, rSO2 monitors and external devices which output analog voltage signal.

The device will be available for use by medical personnel on patients within a medical facility on all patient populations.

The Nihon Kohden CSM-1901 Bedside Monitor is intended to monitor, display and record physiological data to provide cardiac and vital signs monitoring within a medical facility. The device is intended to produce a visual record of the electrical signal produced by the heart and monitor the electrocardiogram to generate visible alarms when an arrhythmia exists. The device is also intended to monitor heart rate, blood oxygen saturation (SpO2), noninvasive blood pressure (NIBP), invasive blood pressure (IBP), body temperature, BIS, cardiac output (CO), oxygen concentration (FiO2), carbon dioxide concentration (CO2), EtCO2, respiratory rate, inspired and expired anesthetic agents and anesthetic gases including N20, halothane, isoflurane, enflurane and desflurane. The device also displays patient data from external devices such as ventilators, TOF monitors, and EEG measuring unit.

The device may generate and audible and/or visual alarm when a measured rate falls outside preset limits.

The device will be available for use by trained medical facility on all patient populations. including adult, neonate, infant, child, and adolescent subgroups.

The Nihon Kohden Smart Cable NMT Module (NMT Module) and Accessories is an optional accessory for the Nihon Kohden bedside monitoring systems. The Smart Cable NMT Module and Accessories TOF (Train of Four) are based on EMG technology. With this system, the user can apply electrical stimulation on the ulnar nerve to detect the muscle's action potential. The reaction to the electrical impulse can be visualized on the connected monitoring system. The Smart Cable NMT Module and Accessories can assist medical personnel to quantitatively determine the level of muscle relaxation. This information can be used to determine the dose of muscle relaxants and regional anesthetics when performing anesthesia in a clinical setting. It is intended for use by medical personnel in the operating room, recovery room, or intensive care unit.

The NMT Module is a system comprised of NMT Module, Main Cable, Holder, and EMG Electrode. The NMT module is connected to an electrode via Main Cable. The electrode is a single-use electrode array and each array includes two stimulating electrodes, two recording electrodes, and one ground electrode. The NMT module can transmit an electrical stimulation pulse to the patient and can receive EMG signals via the electrode array. The captured data from the disposable electrode is sent to the monitoring system via the Smart Cable interface connector. The various stimulation settings are also sent to the monitoring system to display.

The AF-201P NMT Module is used to control the electrical stimulation and to measure the response. The operational setting is controlled via buttons on the module or a touch screen.

The Life Scope BSM-3000 Series Bedside Monitoring System is intended to monitor, display and record physiological data to provide cardiac and vital signs monitoring within a medical facility. The device is intended to produce a visual record of the electrical signals produced by the heart and monitor the electrocardiogram to generate visible and/or audible alarms when an arrhythmia exists. The device is also intended to monitor heart rate, pulse rate, blood oxygen saturation (SpO2), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), body temperature, Cardiac Output (CO), oxygen concentration (O2), CO2 and EtCO2, respiratory rate, BIS and inspired and expired anesthetic agents and gases including CO2, O2, N2O, Halothane, Isoflurane, Enflurane, Sevoflurane and Desflurane. Anesthetic agents and gases are detected using the cleared AG-920RA Anesthetic Agent Detection System. The device can interface to external equipment to display numerical and waveform data and alarms from the external devices. Supported external devices include AG-920RA Anesthetic Agent Detection System, Ventilators, CO2 Monitors, TOF Monitors, BIS Monitors, CCO/SvO2 Monitors, EEG monitoring device, tcPO2 monitors, rSO2 monitors and external devices with output analog voltage signal and continuous NIBP Monitors. The device may generate an audible and/or visual alarm when a measured rate falls outside preset limits. This device may also be used to condition and transmit physiological signals via radio frequency.

The Life Scope BSM-6000 Series Bedside Monitoring System is intended to monitor, display and record physiological data to provide cardiac and vital signs monitoring within a medical facility. The device is intended to produce a visual record of the electrical signals produced by the heart and monitor the electrocardiogram to generate visible and/or audible alarms when an arrhythmia exists. The device is also intended to monitor heart rate, pulse rate, blood oxygen saturation (SpO2), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), body temperature, Cardiac Output (CO), oxygen concentration (FiO2), CO2 and EtCO2, respiratory rate, BIS and inspired and expired anesthetic agents and gases including CO2, O2, N2O, Halothane, Isoflurane, Enflurane, Sevoflurane and Desflurane. Anesthetic agents and gases are detected using the cleared AG-920RA Anesthetic Agent Detection System. The device can interface to external equipment to display numerical and waveform data and alarms from the external devices. Supported external devices include AG-920RA Anesthetic Agent Detection System, Ventilators, CO2 Monitors, TOF Monitors, BIS Monitors, CCO/SvO2 Monitors and continuous NIBP Monitors. The device may generate an audible and/or visual alarm when a measured rate falls outside preset limits. This device may also be used to condition and transmit physiological signals via radiofrequency.

The Nihon Kohden CSM-1901Series is a device which continuously monitors physiological information of a patient and is used in an operation room, a recovery room, general wards, ICU, CCU, HCU, NICU and an emergency room. This bedside monitor is placed near the patient and is intended to display patient's vital signs. This device can also be connected to other external patient monitoring devices. In addition, this device can communicate patient's data to a central monitoring station via network to monitor multiple patients.

The provided text describes the acceptance criteria and study data for the Smart Cable NMT Module and Accessories, as well as the Life Scope BSM-3000, BSM-6000, and CSM-1901 Bedside Monitors. However, the document is a 510(k) summary for substantial equivalence, which primarily focuses on comparing the new device to existing predicate devices and demonstrating that it is as safe and effective. It does not contain an explicit table of acceptance criteria and reported device performance in the format typically used for a detailed study report.

Instead, the document states that various tests were performed and that the devices "met all the acceptance criteria" or "performed within specifications." It also notes that "No clinical tests have been submitted, referenced or relied on in the premarket notification submission for a determination of substantial equivalence." This implies that the acceptance criteria for performance were likely derived from industry standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-40, ANSI/AAMI EC12:2000), internal company specifications, and comparison to predicate devices, rather than from a standalone clinical study with an explicit set of primary and secondary endpoints and predefined performance metrics.

Therefore, many of the requested details such as sample size for the test set, data provenance, number and qualifications of experts, adjudication methods, MRMC studies, standalone algorithm performance, and ground truth establishment from actual patient data (for algorithm training/testing) are not present in this 510(k) summary. This is typical for a 510(k) submission where substantial equivalence is demonstrated through non-clinical performance and engineering validation rather than through new clinical studies, especially for devices where modifications are minor or where performance can be adequately assessed through bench testing and comparisons to established technological characteristics of predicates.

Below is an attempt to address the request based on the information available in the provided text, while also explicitly stating what information is not provided.

Acceptance Criteria and Device Performance (Based on available information):

The document does not present a formal table of acceptance criteria with corresponding device performance results for each specific metric. Instead, it broadly states that the devices underwent various non-clinical tests and met the acceptance criteria. The acceptance criteria were primarily based on compliance with relevant industry standards and comparison to the performance specifications of predicate devices.

Summary of Device Performance and Acceptance (Inferred from the document):

Details Regarding the Study/Testing:

1. A table of acceptance criteria and the reported device performance:

   • As noted above, a formal table is not provided. The document states that various tests (electrical safety, EMC, software V&V, operational performance, environmental performance, biocompatibility, shelf life, electrode performance for NMT module; and software integration, EMC, environmental, safety for Bedside Monitors) were conducted and that the devices "met all the acceptance criteria" or "performed within specifications." The specific quantitative pass/fail thresholds for each test are not detailed in this summary.

2. Sample sized used for the test set and the data provenance:

   • Sample Size: Not explicitly stated for any of the performance tests (e.g., how many devices were tested, how many signal samples were used for performance evaluation).
   • Data Provenance: The tests are described as non-clinical (bench testing, software validation). There is no indication of patient data being used for device performance validation as part of this 510(k) submission. The document explicitly states: "No clinical tests have been submitted, referenced or relied on in the premarket notification submission for a determination of substantial equivalence."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable as no clinical study or expert-adjudicated ground truth dataset is described for device performance validation. The ground truth for engineering and performance tests would be defined by the measurement standards and validation protocols themselves (e.g., a calibrated instrument reading as ground truth for a measurement accuracy test).

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable as no clinical study or expert adjudication process for a test set is described.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No MRMC study was done, as explicitly stated: "No clinical tests have been submitted, referenced or relied on in the premarket notification submission." The device is a monitor, not an AI-assisted diagnostic tool that would typically involve human reader improvement studies.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Performance validation was conducted via non-clinical testing against specifications and standards, which generally assesses the algorithm's (or device's) performance in isolation under controlled conditions (e.g., accuracy of readings, alarm thresholds). Specific "standalone performance" metrics (like sensitivity/specificity for a diagnostic algorithm) are not detailed as the device is a measurement and monitoring system.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For the non-clinical tests described, the "ground truth" would be the known inputs or reference values from calibrated test equipment, as per engineering and quality assurance standards. No medical "ground truth" (e.g., expert consensus, pathology, outcomes data) from patients was used for device verification or validation in this submission.

8. The sample size for the training set:

   • Not applicable. The document describes a medical device (monitor) with firmware/software, not an AI/ML algorithm that would typically require a distinct training set (beyond standard software development and testing).

9. How the ground truth for the training set was established:

   • Not applicable, as there is no specific "training set" described for an AI/ML algorithm.

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The Smart-C is a mini C-arm X-ray system designed to provide physicians with real time general fluoroscopic visualization of adult and pediatric patients. It is intended to aid physicians and surgeons during diagnostic procedures, therapeutic treatment, or surgical procedures of the limbs, extremities, or shoulders including but not limited to, orthopedics and emergency medicine. The Smart-C is intended to be used on a table or other hard flat surface. It may also be used with the optional support stand.

The Smart-C is an ultra-portable, battery-powered, mobile fluoroscopic mini C-arm system. The main component is a mini C-arm that consists of a CMOS flat panel detector aligned with an X-ray source monoblock to be used for image acquisition. The system can be hand-transported for imaging at the point of care. The primary operator workstation is a tablet computer that receives the images from the C-arm via wireless transfer protocol. The system includes a wireless footswitch to initiate image acquisition, making the entire system cord-free during operation. It comes with 2 battery packs, a table-top battery charger, and a tablet docking station. An optional Monitor Cart is provided as an accessory. The Smart-C monitor cart includes a 27" full-color touchscreen monitor, a keyboard for data entry, a printer for hard-copy of the x-ray images, and a battery charger for the Smart-C battery packs. The whole cart is battery-powered, to provide a completely cord-free user experience.

The provided text describes the 510(k) premarket notification for the Smart-C™ X-ray Imaging System and its comparison to a predicate device, the Orthoscan Mobile DI Mini C-arm. The document focuses on demonstrating substantial equivalence, rather than a traditional AI/ML performance study with specific acceptance criteria metrics like sensitivity, specificity, or AUC.

Therefore, the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in terms of explicit performance metrics, sample sizes for training/test sets, expert adjudication methods, MRMC studies, standalone algorithm performance, and ground truth establishment for a medical AI device cannot be fully extracted from this document. This is because the Smart-C is an imaging device, not an AI/ML algorithm that interprets images. The "performance" discussed relates to image quality and usability, compared to a predicate device, rather than diagnostic accuracy of an algorithm.

However, I can extract information related to the device's evaluation methods and the qualitative assessment of its performance against the predicate, which serves as its "acceptance criteria" for substantial equivalence.

Here's an attempt to answer the questions based on the available text, with caveats where the specific details are not provided:

Device: Smart-C™ X-ray Imaging System

1. A table of acceptance criteria and the reported device performance

The acceptance criteria are not explicitly stated as quantitative performance metrics (e.g., specific image resolution values to be met). Instead, the performance is evaluated against the predicate device and relevant standards to demonstrate substantial equivalence. The "acceptance" is qualitative: that the device's image quality and usability are "at least as good as" the predicate device and meet applicable safety and performance standards.

"Based on physician feedback, the clinical images obtained with the Smart-C were at least as good as the predicate device." |
| Safety and Efficacy: Compliance with relevant standards and guidance documents. | The device "meets the same recognized performance and safety standards, and to conform to FDA guidance regarding solid-state x-ray imaging systems." It has been tested for compliance with "applicable IEC series of x-ray performance standards, including IEC60601-2-54" and "all applicable 21CFR Subchapter J performance standards." Risk analysis and design mitigations were successfully tested. |
| Usability: Equivalent or improved workflow/ease of imaging, given differences like wireless technology and battery power. | The wireless image transfer "improves the workflow and ease of imaging." "The clinical utility of the Smart-C was demonstrated by performing a Clinical Imaging Evaluation. Cadaver subjects were chosen to represent the range of extremity imaging, including shoulders." Pediatric Imaging Usability Evaluation was performed for neonatal and infant patients. "There were no new concerns regarding patient positioning, including for neonatal and infant patients." "The Smart-C has been evaluated by numerous physicians and surgeons for image quality and usability on anthropomorphic phantoms, image quality phantoms, and cadaver subjects in clinical settings. They determined that it performs at least as well as the predicate device, and that it is efficacious for the intended uses." |
| Technical Equivalence: Fundamental scientific technology and core components similar to predicate. | Both devices "use the same fundamental scientific technology of generating fluoroscopic x-ray images using an x-ray source monoblock and flat-panel x-ray imaging detector in a fixed C-arm configuration." Designs are "based on the same modern technologies using a compact monoblock x-ray generator and flat-panel x-ray detector, operating at similar power levels." |

2. Sample sizes used for the test set and the data provenance

• Test Set (Clinical Imaging Evaluation):
  • Sample Size:
    • "Cadaver subjects were chosen to represent the range of extremity imaging, including shoulders." (Specific number not provided).
    • A "Pediatric Imaging Usability Evaluation was performed" for "neonatal and infant patients." (Specific number of subjects not provided).
    • For the tablet display evaluation, "all presented cases" were evaluated (number of cases not specified).
    • "Anthropomorphic phantoms" and "image quality phantoms" were also used.
  • Data Provenance: Not explicitly stated (e.g., country of origin). The evaluation involved "clinical" settings using cadavers. The pediatric study was also an "Evaluation," implying a simulated or controlled setting, not necessarily retrospective or prospective patient data from a real clinic.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts:
  • Tablet Display Evaluation: "2 independent board-certified physicians."
  • Image Quality Evaluation (Smart-C): "independent physicians" (number not specified).
  • General Evaluation: "numerous physicians and surgeons" (number not specified).
• Qualifications of Experts: "board-certified physicians" for the display evaluation. For other evaluations, they are referred to simply as "physicians" or "physicians and surgeons."

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• For the tablet display evaluation, it states, "The conclusion of the expert evaluators is that the image quality of the tablet is diagnostic in all presented cases..." This suggests that both experts agreed, or their consensus was sufficient. No formal adjudication method like "2+1" or "3+1" is described.
• For other aspects, "physician feedback" was used, implying a qualitative assessment rather than a structured adjudication process for ground truth.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• No MRMC comparative effectiveness study was done with AI assistance. This device is an X-ray imaging system, not an AI-powered diagnostic algorithm. The evaluations were performed to establish image quality and usability of the device itself compared to a predicate device, not to evaluate human reader performance with or without AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not applicable. The Smart-C is a piece of hardware (fluoroscopic X-ray system) that produces images for human interpretation, not a standalone diagnostic algorithm. Its "performance" refers to the quality of the images it generates.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• The "ground truth" for the evaluations was primarily expert judgment/consensus regarding image diagnostic quality and usability. This was based on:
  • "Anthropomorphic phantoms" and "image quality phantoms" (for objective image quality measures like contrast and spatial resolution).
  • "Cadaver subjects" (for clinical imaging evaluation and simulating patient positioning).
  • "Neonatal and infant patients" (for pediatric usability evaluation, likely simulated or using models).
  • Physicians' informal "feedback" and "conclusion" on images and usability.

8. The sample size for the training set

• Not applicable. This document describes the evaluation of a medical imaging device, not the development or training of an AI/ML algorithm. Therefore, there is no "training set" in the context of machine learning.

9. How the ground truth for the training set was established

• Not applicable. As a hardware medical imaging device, there is no AI/ML training set or associated ground truth establishment process in the context of this FDA submission.

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The MALDI Biotyper CA System is a mass spectrometer systems using matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF) for the identification of microorganisms cultured from human specimens.

The MALDI Biotyper CA System is a qualitative in vitro diagnostic device indicated for use in conjunction with other clinical and laboratory findings to aid in the diagnosis of bacterial and yeast infections.

The MBT-CA System is a mass spectrometer system using matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF) for the identification of microorganisms cultured from human specimens. The system uses a different methodology for organism identification based on unique protein patterns of the microorganisms obtained from mass spectrometry. The test organism's spectrum (a pattern of mass peaks) is compared with a reference spectra library (database). Using biostatistical analysis, a probability ranking of the organism identification is generated. The probability ranking is represented as a log(score) between 0.00 and 3.00. Organism identification is reported with high confidence if the log(score) is ≥2.00. An organism identification is reported with low confidence if the log(score) is between 1.70 and

Here's a breakdown of the acceptance criteria and the study details for the MALDI Biotyper CA (MBT-CA) System, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state pre-defined acceptance criteria in terms of numerical thresholds for sensitivity, specificity, or overall accuracy. Instead, it presents performance results from various studies (reproducibility, challenge panel, method comparison) and concludes that the device performs acceptably.

However, based on the reported performance in the Method Comparison study, common metrics for identification systems would be:

Note: The "acceptance criteria" presented above are inferred from the strong performance and conclusions drawn in the document, rather than explicitly stated numerical targets prior to testing.

2. Sample Size Used for the Test Set and Data Provenance

• Method Comparison Study (Overall Isolate Performance):

  • Sample Size: 2091 fresh and stored organisms.
  • Data Provenance: Organisms were tested at four (4) US clinical test sites and an in-house laboratory. Isolates were sub-cultured and sent to an interim reference laboratory and then to a sequencing reference laboratory for ground truth determination. This indicates prospective and retrospective data collection with a US origin.

• Reproducibility Study:

  • Sample Size: 9 unique organisms (REPRO-02 excluded). Each organism tested in duplicate, 5 days, 2 runs/day, 3 sites (9 organisms x 2 replicates x 5 days x 2 runs x 3 sites = 540 measurements). Total MBT-CA IDs for summary = 179/180 per site.
  • Data Provenance: Conducted at three (3) clinical study sites (US, likely, given the FDA submission context). The organisms were "well-characterized," suggesting they might be reference strains or previously identified clinical isolates.

• Challenge Panel Study:

  • Sample Size: 46 organisms.
  • Data Provenance: Selected from stored organisms from the clinical study, prepared by the interim reference laboratory. Tested at three (3) study sites (US, likely).

• Biological/Technical Equivalency Studies:

  • Sample Size: 34 species for laser equivalency (4080 spectra). Multiple species for target equivalency (e.g., 1000 measurements for repeatability/precision, 1500 for LOD, 2500 for sample stability prior to matrix, 3000 for post-matrix stability, 50 FDA cleared organisms, 1500 for mass accuracy/edge effects). Nocardia Study: 30 strains covering 6 species, resulting in ~15,000 measurements.
  • Data Provenance: Not explicitly stated for specific origin, but these are technical validation studies performed by the manufacturer, likely controlled lab settings.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

• Method Comparison Study:

  • The ground truth was established by sequencing (16S rRNA or ITS sequencing and protein gene sequencing). This relies on established molecular biology techniques, not human expert interpretation. While experts run and interpret these sequences, the core ground truth is the genetic information itself. The document does not specify a number or qualification of "experts" in the sense of clinical reviewers for ground truth determination but implies reliance on the robust and objective results of gene sequencing performed by a sequencing reference laboratory.

• Reproducibility Study:

  • Organisms were "well-characterized." The ground truth was presumably established by prior definitive identification methods, likely including gene sequencing or reputable reference lab methods. No mention of independent experts for this study's ground truth.

• Challenge Panel Study:

  • Organism identifications were "blinded to test sites," and the panel was prepared by the study interim reference laboratory. The ground truth was established by the reference lab, again likely through gold standard methods like sequencing.

4. Adjudication Method for the Test Set

The document does not describe an explicit adjudication method involving multiple human readers or a specific consensus process for discrepancies in the generated log(scores) or identifications against a human-read ground truth. Instead:

• The ground truth for the organism identity itself (reference algorithm) was established by molecular sequencing.
• The device's log(score) provides a quantitative measure of confidence. If the log(score) is too low (

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The Stealth System S300 is indicated for use on adult patients who may be asymptomatic or who may suffer from transient symptoms such as palpitations, dizziness, anxiety, fatigue, syncope, light-headedness, shortness of breath or who are at risk of developing atrial fibrillation and where a software-assisted analysis of an ambulatory ECG could identify potential cardiac causes of these symptoms. It includes a prescription only, single use, continuous ECG recorder that can be worn up to 7 days during activities of daily living.

The Stealth System S300 consists of three components: (1) Sensor, (2) Smart Cable, and (3) StealthView personal computer software (PC Software). No component of the system is provided sterile. The Sensor is a 7-day, wearable, single use, disposable recorder that detects and records ECG signals and records patient event markers. Recorded data is retrieved by connecting the Sensor to StealthView software using the Smart Cable after the Sensor has been removed from the patient. StealthView software analyzes the recorded ECG signal and provides a report of heart rhythms for clinician review.

The provided text describes a 510(k) premarket notification for the Stealth System S300, a device designed for continuous ambulatory ECG recording and analysis to aid in the diagnosis of cardiac arrhythmias.

Here's a breakdown of the acceptance criteria and study information, based only on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state a table of "acceptance criteria" with specific numerical targets. Instead, it discusses the performance study by stating: "The Stealth System S300 ECG recorder and ECG analysis performance was quantified for the claimed analysis metrics. The resulting statistics demonstrate sensitivity and positive predictivity levels that satisfy requirements and minimize safety or efficacy concerns."

However, it does provide a comparison table with the predicate device (ZIO SkyRunner (SR) Electrocardiogram (ECG) Monitoring Service) for various technological elements and detected rhythms. This implicitly defines the "performance" as being comparable to the predicate for all listed arrhythmias.

Note: The predicate device (ZIO ECG Utilization Service System) also detects "AV block," "Ventricular Trigeminy," "Ventricular Bigeminy," and "VF / TdP / PVT (CU)" which are not listed as detected by the Stealth System S300. The document states "None of the differences outlined in the tables above raise new questions of safety or effectiveness," implying that the lack of these detections for the Stealth System S300 does not preclude substantial equivalence for the specific indications claimed.

2. Sample Size Used for the Test Set and Data Provenance

The document does not provide a specific sample size for a "test set" in the context of an arrhythmia detection study. It states that "Bench testing alone is sufficient and was completed in accordance with applicable FDA recognized consensus standards for ambulatory ECG recorder and analysis systems." This implies that the performance evaluation was based on bench-level testing rather than a clinical study with patient data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

The document does not mention the use of experts to establish ground truth for a test set. This is consistent with the statement that no animal or clinical studies were conducted, and that bench testing was deemed sufficient.

4. Adjudication Method for the Test Set

No adjudication method is mentioned as a formal clinical study with human interpretation and adjudication was not performed according to the provided text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. The document explicitly states: "Animal and clinical studies were not conducted for the Stealth System S300 submission. Bench testing alone is sufficient..." Therefore, there is no effect size reported for human readers improving with AI vs. without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The assessment described in the document primarily focuses on the standalone performance of the Stealth System S300's ECG analysis software (StealthView). The statement "The Stealth System S300 ECG recorder and ECG analysis performance was quantified for the claimed analysis metrics" refers to the algorithm's performance. The system provides an "analysis for review by the clinician to render a diagnosis," indicating an algorithm-only analysis that is then reviewed by a human.

7. Type of Ground Truth Used

The document indicates that the performance evaluation was based on "bench testing." This typically involves using simulated or validated ECG signals with known arrhythmias to test the algorithm's detection accuracy. It does not mention expert consensus, pathology, or outcomes data as ground truth for this performance study.

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set of the StealthView algorithm.

9. How the Ground Truth for the Training Set Was Established

The document does not describe how the ground truth for the training set was established.

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Health2Sync Mobile Application is data management software that is intended for use in home and professional settings to aid people with diabetes and their healthcare professionals in the review, analysis and evaluation of glucose test results to support an effective diabetes management program. The Health2Sync Smart Cable allows users to upload blood glucose data from compatible FDA cleared meters to the Health2Sync Mobile Application on their iPhone operating system platform.

Health2Sync Mobile Application is not intended to provide treatment decisions nor is it to be used as a substitute for professional healthcare advice.

The Health2Sync Mobile Application and Smart Cable (Mobile App and adapters) allows the transfer of blood glucose readings from the compatible glucose meter to smartphone via Smart Cable.

The App features enable the user to view and analyze blood glucose readings from different meal time periods, other features including lifestyle diary, interpretable graphs option, inviting and sharing data with partners, and emailing reports are available for viewing and analyzing blood glucose readings within the different time slots.

The system includes: 1) Health2Sync Mobile Application (through Apple store only), 2) Smart Cable, 3) Smart Cable 3.5mm connector (optional) and 4) Smart Cable and Application Quick Start Guide

Compatible Meters include: OMNIS Health Embrace BGMS Meter, (K113098) OMNIS Health Embrace EVO BGMS Meter (K090043), and Medline EvenCare G2 BGMS meter (K113208)

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Device: Health2Sync Mobile Application and Smart Cable for Diabetes Management
Intended Use: Data management software for home and professional settings to aid people with diabetes and healthcare professionals in reviewing, analyzing, and evaluating glucose test results to support diabetes management. The Smart Cable allows uploading blood glucose data from compatible FDA-cleared meters to the Health2Sync Mobile Application on iPhone. It is not intended to provide treatment decisions or substitute professional healthcare advice.

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on demonstrating functional equivalence and safety rather than specific numerical acceptance criteria for a diagnostic performance. Acceptance is generally implied by successfully passing various verification tests.

2. Sample Size Used for the Test Set and Data Provenance

• Data Transmission Memory Rollover Synchronization Verification:

  • Test Set Sample Size: 2 meters per model (total 6 meters) with fully loaded data, and 15 meters across 3 models with partially loaded data.
  • Data Provenance: Not explicitly stated, but implied to be laboratory-generated or controlled data for testing purposes within the manufacturer's verification process. No mention of country of origin or retrospective/prospective human data.

• User Performance Evaluation:

  • Test Set Sample Size: 21 participants.
  • Data Provenance: Not explicitly stated, but implied to be a prospective user study conducted by the manufacturer for evaluation. No mention of country of origin.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

This type of information is generally not applicable for this device. The device's primary function is data transfer and display, not a diagnostic interpretation that requires expert ground truth.

• For the Data Transmission testing, the "ground truth" is the data stored on the blood glucose meters themselves, and the accuracy is verified against this known data. No human experts are involved in establishing this ground truth.
• For the User Performance Evaluation, the "ground truth" is the successful completion of tasks as defined by the study protocol. No external experts are required to establish this.
• For EMC and Readability, the ground truth is established by standardized testing protocols and algorithms (e.g., Flesch-Kincaid Grade Level), not human experts.

4. Adjudication Method for the Test Set

Not applicable. As noted above, the tests focus on functional verification, user task completion, and adherence to technical standards rather than subjective assessments requiring adjudication.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. The document does not describe any study involving human readers or comparing AI-assisted performance against unaided human performance. The device is a data management tool, not an AI diagnostic aid in the traditional sense that would warrant an MRMC study.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, the described verification tests for "Data Transmission Memory Rollover Synchronization" and "Electromagnetic Compatibility (EMC)" represent standalone performance evaluations of specific device components (Smart Cable, Mobile App's data handling). The "Readability Assessment" is also a standalone evaluation of the documentation.

The "User Performance Evaluation" implicitly involves a human-in-the-loop, but the overall assessment of the device's core data management functions (e.g., accurate data transfer) is conducted in a standalone manner against predefined criteria.

7. The Type of Ground Truth Used

• Data Transmission Memory Rollover Synchronization Verification: The ground truth was the known data stored on the compatible blood glucose meters. The transferred data was compared against this known source for accuracy.
• User Performance Evaluation: The ground truth was the successful completion of predefined user tasks according to the device's instructions for use.
• Electromagnetic Compatibility (EMC): The ground truth was established by international and national safety standards for electrical equipment.
• Readability Assessment: The ground truth was established by the Flesch-Kincaid Grade Level algorithm, a standardized metric for readability.

8. The Sample Size for the Training Set

The document does not describe a "training set" in the context of an AI/machine learning model. The Health2Sync Mobile Application appears to be a data management software that processes and displays glucose readings rather than learning patterns from a training dataset. Therefore, this information is not applicable.

9. How the Ground Truth for the Training Set was Established

Since there is no mention of a training set or an AI/machine learning component that requires one, this information is not applicable.

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